scholarly journals Deciphering Cell Lineage Specification during Male Sex Determination with Single-Cell RNA Sequencing

Cell Reports ◽  
2018 ◽  
Vol 22 (6) ◽  
pp. 1589-1599 ◽  
Author(s):  
Isabelle Stévant ◽  
Yasmine Neirijnck ◽  
Christelle Borel ◽  
Jessica Escoffier ◽  
Lee B. Smith ◽  
...  
Keyword(s):  
Sex Determination ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Lineage ◽  
Lineage Specification ◽  
Single Cell Rna Sequencing ◽  
Male Sex

scholarly journals Deciphering cell lineage specification during male sex determination with single-cell RNA sequencing

2017 ◽  
Author(s):  
Isabelle Stévant ◽  
Yasmine Neirjinck ◽  
Christelle Borel ◽  
Jessica Escoffier ◽  
Lee B. Smith ◽  
...  
Keyword(s):  
Sex Determination ◽  
Single Cell ◽  
Progenitor Cells ◽  
Rna Sequencing ◽  
Cell Fate ◽  
Time Course ◽  
Cell Lineage ◽  
Lineage Specification ◽  
Cell Fate Decisions ◽  
Single Cell Rna Sequencing

SummaryThe gonad is a unique biological system for studying cell fate decisions. However, major questions remain regarding the identity of somatic progenitor cells and the transcriptional events driving cell differentiation. Using time course single cell RNA sequencing on XY mouse gonads during sex determination, we identified a single population of somatic progenitor cells prior sex determination. A subset of these progenitors differentiate into Sertoli cells, a process characterized by a highly dynamic genetic program consisting of sequential waves of gene expression. Another subset of multipotent cells maintains their progenitor state but undergo significant transcriptional changes that restrict their competence towards a steroidogenic fate required for the differentiation of fetal Leydig cells. These results question the dogma of the existence of two distinct somatic cell lineages at the onset of sex determination and propose a new model of lineage specification from a unique progenitor cell population.

Using single-cell RNA sequencing to unravel cell lineage relationships in the respiratory tract

2020 ◽  
Vol 48 (1) ◽  
pp. 327-336 ◽  
Author(s):  
L.E. Zaragosi ◽  
M. Deprez ◽  
P. Barbry
Keyword(s):  
Respiratory Tract ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Lineage ◽  
Neuroendocrine Cells ◽  
Basal Cells ◽  
Multiciliated Cells ◽  
Single Cell Rna Sequencing ◽  
Rare Cells ◽  
Genetic Labeling

The respiratory tract is lined by a pseudo-stratified epithelium from the nose to terminal bronchioles. This first line of defense of the lung against external stress includes five main cell types: basal, suprabasal, club, goblet and multiciliated cells, as well as rare cells such as ionocytes, neuroendocrine and tuft/brush cells. At homeostasis, this epithelium self-renews at low rate but is able of fast regeneration upon damage. Airway epithelial cell lineages during regeneration have been investigated in the mouse by genetic labeling, mainly after injuring the epithelium with noxious agents. From these approaches, basal cells have been identified as progenitors of club, goblet and multiciliated cells, but also of ionocytes and neuroendocrine cells. Single-cell RNA sequencing, coupled to lineage inference algorithms, has independently allowed the establishment of comprehensive pictures of cell lineage relationships in both mouse and human. In line with genetic tracing experiments in mouse trachea, studies using single-cell RNA sequencing (RNAseq) have shown that basal cells first differentiate into club cells, which in turn mature into goblet cells or differentiate into multiciliated cells. In the human airway epithelium, single-cell RNAseq has identified novel intermediate populations such as deuterosomal cells, ‘hybrid’ mucous-multiciliated cells and progenitors of rare cells. Novel differentiation dynamics, such as a transition from goblet to multiciliated cells have also been discovered. The future of cell lineage relationships in the respiratory tract now resides in the combination of genetic labeling approaches with single-cell RNAseq to establish, in a definitive manner, the hallmarks of cellular lineages in normal and pathological situations.

scholarly journals Bayesian gamma-negative binomial modeling of single-cell RNA sequencing data

BMC Genomics ◽  
2020 ◽  
Vol 21 (S9) ◽  
Author(s):  
Siamak Zamani Dadaneh ◽  
Paul de Figueiredo ◽  
Sing-Hoi Sze ◽  
Mingyuan Zhou ◽  
Xiaoning Qian
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Data Augmentation ◽  
Negative Binomial ◽  
Cell Lineage ◽  
Simulated Data ◽  
Molecular Heterogeneity ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Zero Counts

Abstract Background Single-cell RNA sequencing (scRNA-seq) is a powerful profiling technique at the single-cell resolution. Appropriate analysis of scRNA-seq data can characterize molecular heterogeneity and shed light into the underlying cellular process to better understand development and disease mechanisms. The unique analytic challenge is to appropriately model highly over-dispersed scRNA-seq count data with prevalent dropouts (zero counts), making zero-inflated dimensionality reduction techniques popular for scRNA-seq data analyses. Employing zero-inflated distributions, however, may place extra emphasis on zero counts, leading to potential bias when identifying the latent structure of the data. Results In this paper, we propose a fully generative hierarchical gamma-negative binomial (hGNB) model of scRNA-seq data, obviating the need for explicitly modeling zero inflation. At the same time, hGNB can naturally account for covariate effects at both the gene and cell levels to identify complex latent representations of scRNA-seq data, without the need for commonly adopted pre-processing steps such as normalization. Efficient Bayesian model inference is derived by exploiting conditional conjugacy via novel data augmentation techniques. Conclusion Experimental results on both simulated data and several real-world scRNA-seq datasets suggest that hGNB is a powerful tool for cell cluster discovery as well as cell lineage inference.

Using Single-Cell and Spatial Transcriptomes to Understand Stem Cell Lineage Specification During Early Embryo Development

2020 ◽  
Vol 21 (1) ◽  
pp. 163-181
Author(s):  
Guangdun Peng ◽  
Guizhong Cui ◽  
Jincan Ke ◽  
Naihe Jing
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Fate ◽  
Cell Lineage ◽  
Stem Cell Differentiation ◽  
Early Embryo ◽  
Stem Cell Lineage ◽  
Single Cell Rna Sequencing ◽  
Cell Organization

Embryonic development and stem cell differentiation provide a paradigm to understand the molecular regulation of coordinated cell fate determination and the architecture of tissue patterning. Emerging technologies such as single-cell RNA sequencing and spatial transcriptomics are opening new avenues to dissect cell organization, the divergence of morphological and molecular properties, and lineage allocation. Rapid advances in experimental and computational tools have enabled researchers to make many discoveries and revisit old hypotheses. In this review, we describe the use of single-cell RNA sequencing in studies of molecular trajectories and gene regulation networks for stem cell lineages, while highlighting the integratedexperimental and computational analysis of single-cell and spatial transcriptomes in the molecular annotation of tissue lineages and development during postimplantation gastrulation.

scholarly journals Rainbow-Seq: Combining Cell Lineage Tracing with Single-Cell RNA Sequencing in Preimplantation Embryos

iScience ◽  
2018 ◽  
Vol 7 ◽  
pp. 16-29 ◽  
Author(s):  
Fernando H. Biase ◽  
Qiuyang Wu ◽  
Riccardo Calandrelli ◽  
Marcelo Rivas-Astroza ◽  
Shuigeng Zhou ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Lineage ◽  
Lineage Tracing ◽  
Preimplantation Embryos ◽  
Single Cell Rna Sequencing

scholarly journals Current Epigenetic Insights in Kidney Development

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1281
Author(s):  
Katrina Chan ◽  
Xiaogang Li
Keyword(s):  
Single Cell ◽  
Kidney Development ◽  
Kidney Diseases ◽  
Cell Lineage ◽  
Epigenetic Mechanisms ◽  
Phenotypic Stability ◽  
Lineage Specification ◽  
Adult Kidney ◽  
Single Cell Rna Sequencing ◽  
Histone Modification Patterns

The kidney is among the best characterized developing tissues, with the genes and signaling pathways that regulate embryonic and adult kidney patterning and development having been extensively identified. It is now widely understood that DNA methylation and histone modification patterns are imprinted during embryonic development and must be maintained in adult cells for appropriate gene transcription and phenotypic stability. A compelling question then is how these epigenetic mechanisms play a role in kidney development. In this review, we describe the major genes and pathways that have been linked to epigenetic mechanisms in kidney development. We also discuss recent applications of single-cell RNA sequencing (scRNA-seq) techniques in the study of kidney development. Additionally, we summarize the techniques of single-cell epigenomics, which can potentially be used to characterize epigenomes at single-cell resolution in embryonic and adult kidneys. The combination of scRNA-seq and single-cell epigenomics will help facilitate the further understanding of early cell lineage specification at the level of epigenetic modifications in embryonic and adult kidney development, which may also be used to investigate epigenetic mechanisms in kidney diseases.

108 Single-Cell RNA Sequencing Reveals Blastomere Heterogeneity and Early Lineage Specification Events in Bovine Embryos During Major Embryonic Genome Activation

2018 ◽  
Vol 30 (1) ◽  
pp. 193
Author(s):  
I. Lavagi ◽  
S. Krebs ◽  
K. Simmet ◽  
V. Zakhartchenko ◽  
E. Wolf ◽  
...  
Keyword(s):  
Cell Division ◽  
Single Cell ◽  
Rna Sequencing ◽  
Bovine Embryos ◽  
Lineage Specification ◽  
Embryonic Genome Activation ◽  
Embryonic Genome ◽  
Single Cell Rna Sequencing ◽  
Genome Activation ◽  
Go Terms

During early embryonic stages, gene products generated by the embryo acquire control over embryonic development. At the 8- to 16-cell stage, major embryonic genome activation (EGA) occurs in bovine embryos. Morphological observations, such as size of blastomeres and distribution of microvilli, suggest heterogeneity of individual cells already at this developmental stage. To study this heterogeneity on the transcriptome level, we performed single-cell RNA sequencing (scRNA-seq) of 161 blastomeres from 14 in vitro-produced bovine embryos at Day 2 and Day 3 post-fertilization. After removing the zona pellucida, blastomeres were mechanically separated in Ca2+- and Mg2+-free PBS, individually collected, and lysed. Complementary DNA libraries were prepared by the single cell RNA-barcoding and sequencing (SCRB-Seq) protocol. Exogenous RNA was added for quality control and cell specific barcodes and unique molecular identifiers (UMI) were used to enable pooling of libraries and to exclude PCR duplicates, respectively. After sequencing (Illumina HiSEqn 1500; 50 nt reads; Illumina Inc., San Diego, CA, USA), UMI were counted with the published Drop-seq pipeline (45,000 UMI on average per library) and cells with UMI count <2.000 were removed. Data were normalized based on UMI and non-supervised clustering analyses of single-cell data were performed (SC3 and M3Drop R packages). The transcriptome profiles of all individual cells were assigned to 6 clusters with specific sets of genes. Sorting cells according to their transcriptome profiles by the CellTree R package (Bioconductor; https://bioconductor.org/packages/release/bioc/html/cellTree.html) resulted in a linear pseudo-timeline. Furthermore, this tool identified 6 groups of genes (topics). Each of them showed an over-representation of distinct Gene Ontology (GO) terms; topic 1, “translation” and “cell division”; topic 2, GO terms involved in translation, RNA splicing and cell division; topic 3, “translation”; topic 4, “ATP synthesis coupled proton transport”; topic 5, “mitochondrial translational elongation”; topic 6, “organic hydroxyl compound transport”. Moreover, increased expression of PCDH10 (protocadherin 10) was observed in the biologically pseudo-ordered more advanced blastomeres. This gene is known to be predominantly expressed in the inner cell mass (ICM) at the blastocyst stage, suggesting that these cells might become ICM. In summary, our study reveals developmental heterogeneity and hints to early lineage specification events in bovine embryos at the time of major EGA.

scholarly journals Stromal Heterogeneity in the Human Proliferative Endometrium—A Single-Cell RNA Sequencing Study

2021 ◽  
Vol 11 (6) ◽  
pp. 448
Author(s):  
Suzanna Queckbörner ◽  
Carolina von Grothusen ◽  
Nageswara Rao Boggavarapu ◽  
Roy Mathew Francis ◽  
Lindsay C. Davies ◽  
...  
Keyword(s):  
Menstrual Cycle ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Lineage ◽  
Bioinformatic Analysis ◽  
Matrix Composition ◽  
Cellular Interactions ◽  
Novel Therapy ◽  
Single Cell Rna Sequencing ◽  
Endometrial Regeneration

The endometrium undergoes regular regeneration and stromal proliferation as part of the normal menstrual cycle. To better understand cellular interactions driving the mechanisms in endometrial regeneration we employed single-cell RNA sequencing. Endometrial biopsies were obtained during the proliferative phase of the menstrual cycle from healthy fertile women and processed to single-cell suspensions which were submitted for sequencing. In addition to known endometrial cell types, bioinformatic analysis revealed multiple stromal populations suggestive of specific stromal niches with the ability to control inflammation and extracellular matrix composition. Ten different stromal cells and two pericyte subsets were identified. Applying different R packages (Seurat, SingleR, Velocyto) we established cell cluster diversity and cell lineage/trajectory, while using external data to validate our findings. By understanding healthy regeneration in the described stromal compartments, we aim to identify points of further investigation and possible targets for novel therapy development for benign gynecological disorders affecting endometrial regeneration and proliferation such as endometriosis and Asherman’s syndrome.

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